Recently, the Singapore-based global AI unicorn Deep Intelligent Pharma (DIP) announced the completion of a new $40 million financing round. This round was fully backed by existing investors CDH Baifu, Xinding Capital, Jinyi Capital, and Kaitai Capital, while Index Capital continued to serve as the exclusive financial advisor.
Previously, Deep Intelligent Pharma completed a $50 million Series D round in December 2025, followed by another $60 million financing in February 2026. Only one month after the previous round, the company secured another $40 million investment from institutions. Within just three months, the company has raised a total of $150 million, bringing in many top-tier institutional investors. This strongly reflects the capital market’s recognition and long-term confidence in Deep Intelligent Pharma’s AI-driven “Life Sciences + Materials Science” dual-engine strategy.
1. Brain-Inspired Models Empowering Multiple Industries
Since its founding in 2017, Deep Intelligent Pharma has remained at the forefront of the intersection between AI and scientific research.
In the field of life sciences, the company pioneered a native organizational model combining “AI bionic brain + human experts.” By replacing labor-intensive processes with computational power and building on fundamental scientific mechanisms, the company significantly compresses key stages of clinical research such as clinical trial design cycles and statistical analysis timelines. This approach greatly improves both efficiency and accuracy across the clinical trial pipeline, redefining what an AI-powered CRO (Contract Research Organization) can be.
In materials science, the company has innovatively transferred the microscopic computational complexity paradigm from life sciences to materials research. Through its biomimetic MateriaOS engine, Deep Intelligent Pharma has created what it describes as a “digital wormhole” connecting the microscopic quantum world with macroscopic industrial applications. The platform uses technologies refined in life sciences, including multi-scale modeling, molecular dynamics simulation, and generative AI, as its core foundation. It establishes a unified computational framework that spans the entire chain from atoms to molecules, materials, and final devices.
This system breaks through the efficiency ceiling of traditional materials research based on trial and error. By converting the complexity of biological computation into predictive precision for materials design, the company enables a shift from discovering materials to creating materials.
The modular architecture of the system also supports cross-domain knowledge transfer, providing a general intelligence foundation for vertical industry engines. Downstream applications already cover strategic sectors such as new energy batteries, semiconductor materials, pesticide molecules, and high-temperature alloys.
2. Strong Continued Support from Existing Investors
In this financing round, existing investors CDH Baifu, Xinding Capital, Jinyi Capital, and Kaitai Capital all increased their investments. Their continued support not only recognizes Deep Intelligent Pharma’s past achievements but also represents a strong vote of confidence in the company’s technological barriers, commercialization capability, and long-term development potential.
3. Moving Toward AGI and Opening a New Era of Scientific Discovery
The newly raised capital will mainly be used in three areas. First, the company will continue advancing the development of multi-matrix brain-inspired AGI models, building a multi-matrix intelligent agent system based on the foundations of life sciences and materials science. Second, the company will accelerate its global expansion, strengthening technology delivery and business development in key markets including China, Japan, and the United States. Third, the company will expand its top-tier talent pool, attracting leading global experts at the intersection of AI and scientific research.
Through these efforts, Deep Intelligent Pharma aims to push forward the frontier of AI-driven scientific discovery and move closer to the realization of Artificial General Intelligence (AGI).